Right coronary MR angiography at 7 T: a direct quantitative and qualitative comparison with 3 T in young healthy volunteers.

PURPOSE: To objectively compare quantitative parameters related to image quality attained at coronary magnetic resonance (MR) angiography of the right coronary artery (RCA) performed at 7 T and 3 T. MATERIALS AND METHODS: Institutional review board approval was obtained, and volunteers provided signed informed consent. Ten healthy adult volunteers (mean age ± standard deviation, 25 years ± 4; seven men, three women) underwent navigator-gated three-dimensional MR angiography of the RCA at 7 T and 3 T. For 7 T, a custom-built quadrature radiofrequency transmit-receive surface coil was used. At 3 T, a commercial body radiofrequency transmit coil and a cardiac coil array for signal reception were used. Segmented k-space gradient-echo imaging with spectrally selective adiabatic fat suppression was performed, and imaging parameters were similar at both field strengths. Contrast-to-noise ratio between blood and epicardial fat; signal-to-noise ratio of the blood pool; RCA vessel sharpness, diameter, and length; and navigator efficiency were quantified at both field strengths and compared by using a Mann-Whitney U test. RESULTS: The contrast-to-noise ratio between blood and epicardial fat was significantly improved at 7 T when compared with that at 3 T (87 ± 34 versus 52 ± 13; P = .01). Signal-to-noise ratio of the blood pool was increased at 7 T (109 ± 47 versus 67 ± 19; P = .02). Vessel sharpness obtained at 7 T was also higher (58% ± 9 versus 50% ± 5; P = .04). At the same time, RCA vessel diameter and length and navigator efficiency showed no significant field strength-dependent difference. CONCLUSION: In our quantitative and qualitative study comparing in vivo human imaging of the RCA at 7 T and 3 T in young healthy volunteers, parameters related to image quality attained at 7 T equal or surpass those from 3 T.

Staphylococcal biofilm formation on the surface of three different calcium phosphate bone grafts: a qualitative and quantitative in vivo analysis.

Differences in physico-chemical characteristics of bone grafts to fill bone defects have been demonstrated to influence in vitro bacterial biofilm formation. Aim of the study was to investigate in vivo staphylococcal biofilm formation on different calcium phosphate bone substitutes. A foreign-body guinea-pig infection model was used. Teflon cages prefilled with β-tricalcium phosphate, calcium-deficient hydroxyapatite, or dicalcium phosphate (DCP) scaffold were implanted subcutaneously. Scaffolds were infected with 2 × 10(3) colony-forming unit of Staphylococcus aureus (two strains) or S. epidermidis and explanted after 3, 24 or 72 h of biofilm formation. Quantitative and qualitative biofilm analysis was performed by sonication followed by viable counts, and microcalorimetry, respectively. Independently of the material, S. aureus formed increasing amounts of biofilm on the surface of all scaffolds over time as determined by both methods. For S. epidermidis, the biofilm amount decreased over time, and no biofilm was detected by microcalorimetry on the DCP scaffolds after 72 h of infection. However, when using a higher S. epidermidis inoculum, increasing amounts of biofilm were formed on all scaffolds as determined by microcalorimetry. No significant variation in staphylococcal in vivo biofilm formation was observed between the different materials tested. This study highlights the importance of in vivo studies, in addition to in vitro studies, when investigating biofilm formation of bone grafts.

To say or not to say: a qualitative study on the disclosure of their condition by human immunodeficiency virus-positive adolescents.

PURPOSE: Human immunodeficiency virus (HIV)-positive adolescents face a number of challenges in dealing with their disease, treatment, and developmental tasks. This qualitative study describes some of the reasons why, and the extent to which, adolescents may or may not disclose their condition to others. METHODS: A semistructured interview lasting 40-110 minutes was conducted with each of 29 adolescents 12-20 years old, 22 female and seven male) living in Switzerland. Interviews were tape recorded and transcribed verbatim. The analysis of the content of interviews allowed us to identify salient topics (e.g., disclosure), which were then explored in detail. RESULTS: Of 29 participants, eight had not disclosed their condition to anyone outside the family, 19 had disclosed it to good friends, and 16 had disclosed it to some teachers. Four participants had engaged in public disclosure, and six of 10 sexually active teenagers disclosed their status to their partners. The attitudes toward disclosure among younger adolescents were mostly related to those of the parents, particularly the mother. Older adolescents, engaged in their search for autonomy, tended to decide independently what to say and to whom. Although foster/adoptive parents would often encourage disclosure, biological parents, especially HIV-positive mothers, insisted on not disclosing the adolescent's status for fear of stigma. CONCLUSION: The health care team should systematically address the issue of disclosure with the adolescent and his family (or foster parents), the aim being to balance the right of the adolescent and that adolescent's family to maintain privacy against the concerns of sexual partners, as well as the adolescent's interest in divulging HIV status to relatives, school staff, and friends.

SBML qualitative models: a model representation format and infrastructure to foster interactions between qualitative modelling formalisms and tools.

BACKGROUND: Qualitative frameworks, especially those based on the logical discrete formalism, are increasingly used to model regulatory and signalling networks. A major advantage of these frameworks is that they do not require precise quantitative data, and that they are well-suited for studies of large networks. While numerous groups have developed specific computational tools that provide original methods to analyse qualitative models, a standard format to exchange qualitative models has been missing. RESULTS: We present the Systems Biology Markup Language (SBML) Qualitative Models Package ("qual"), an extension of the SBML Level 3 standard designed for computer representation of qualitative models of biological networks. We demonstrate the interoperability of models via SBML qual through the analysis of a specific signalling network by three independent software tools. Furthermore, the collective effort to define the SBML qual format paved the way for the development of LogicalModel, an open-source model library, which will facilitate the adoption of the format as well as the collaborative development of algorithms to analyse qualitative models. CONCLUSIONS: SBML qual allows the exchange of qualitative models among a number of complementary software tools. SBML qual has the potential to promote collaborative work on the development of novel computational approaches, as well as on the specification and the analysis of comprehensive qualitative models of regulatory and signalling networks.

The Patientʼs Perception of Eosinophilic Esophagitis Related Symptoms: a Qualitative Content Analysis

Background and Aims: The international EEsAI study group is currently developing an activity index for Eosinophilic Esophagitis (EoE). A potential discrepancy between patient and physician reported EoE symptoms has not been assessed yet. Therefore, we aimed to evaluate patient reported items describing their EoE activity and to compare these with the physicianʼs perception. Methods: A questionnaire was sent to 100 EoE patients in Switzerland. EoE-related symptoms dependent and independent of food intake were reported by patients. Results were analyzed using a qualitative content analysis and compared with symptoms reported by international EoE experts in Delphi rounds. Results: The questionnaire response rate was 64/100. The following items were developed by combining categories based on patients answers: food-consistency related dysphagia, frequency and severity of dysphagia, food impaction, strategies to avoid food impaction, food allergy, drinking-related retrosternal pain. The following food categories associated with dysphagia were identified: meat, rice, dry bread, French fries, raw, fibrous foods, others. Sports and psychological stress were identified as triggers for non-food intake related EoE symptoms. A good correlation was found between patient and physicianʼs reported EoE related symptoms. Conclusions: There is a good correlation between patient reported symptoms and the physicianʼs perception of clinical items as reported by international EoE experts. These patient reported outcomes will now be incorporated into the EEsAI questionnaire that measures EoE activity.

MORM--a Petri net based model for assessing OH&S risks in industrial processes: modeling qualitative aspects.

Because of the increase in workplace automation and the diversification of industrial processes, workplaces have become more and more complex. The classical approaches used to address workplace hazard concerns, such as checklists or sequence models, are, therefore, of limited use in such complex systems. Moreover, because of the multifaceted nature of workplaces, the use of single-oriented methods, such as AEA (man oriented), FMEA (system oriented), or HAZOP (process oriented), is not satisfactory. The use of a dynamic modeling approach in order to allow multiple-oriented analyses may constitute an alternative to overcome this limitation. The qualitative modeling aspects of the MORM (man-machine occupational risk modeling) model are discussed in this article. The model, realized on an object-oriented Petri net tool (CO-OPN), has been developed to simulate and analyze industrial processes in an OH&S perspective. The industrial process is modeled as a set of interconnected subnets (state spaces), which describe its constitutive machines. Process-related factors are introduced, in an explicit way, through machine interconnections and flow properties. While man-machine interactions are modeled as triggering events for the state spaces of the machines, the CREAM cognitive behavior model is used in order to establish the relevant triggering events. In the CO-OPN formalism, the model is expressed as a set of interconnected CO-OPN objects defined over data types expressing the measure attached to the flow of entities transiting through the machines. Constraints on the measures assigned to these entities are used to determine the state changes in each machine. Interconnecting machines implies the composition of such flow and consequently the interconnection of the measure constraints. This is reflected by the construction of constraint enrichment hierarchies, which can be used for simulation and analysis optimization in a clear mathematical framework. The use of Petri nets to perform multiple-oriented analysis opens perspectives in the field of industrial risk management. It may significantly reduce the duration of the assessment process. But, most of all, it opens perspectives in the field of risk comparisons and integrated risk management. Moreover, because of the generic nature of the model and tool used, the same concepts and patterns may be used to model a wide range of systems and application fields.

Advanced Kernel Methods For Remote Sensing Image Classification

Résumé Suite aux recentes avancées technologiques, les archives d'images digitales ont connu une croissance qualitative et quantitative sans précédent. Malgré les énormes possibilités qu'elles offrent, ces avancées posent de nouvelles questions quant au traitement des masses de données saisies. Cette question est à la base de cette Thèse: les problèmes de traitement d'information digitale à très haute résolution spatiale et/ou spectrale y sont considérés en recourant à des approches d'apprentissage statistique, les méthodes à noyau. Cette Thèse étudie des problèmes de classification d'images, c'est à dire de catégorisation de pixels en un nombre réduit de classes refletant les propriétés spectrales et contextuelles des objets qu'elles représentent. L'accent est mis sur l'efficience des algorithmes, ainsi que sur leur simplicité, de manière à augmenter leur potentiel d'implementation pour les utilisateurs. De plus, le défi de cette Thèse est de rester proche des problèmes concrets des utilisateurs d'images satellite sans pour autant perdre de vue l'intéret des méthodes proposées pour le milieu du machine learning dont elles sont issues. En ce sens, ce travail joue la carte de la transdisciplinarité en maintenant un lien fort entre les deux sciences dans tous les développements proposés. Quatre modèles sont proposés: le premier répond au problème de la haute dimensionalité et de la redondance des données par un modèle optimisant les performances en classification en s'adaptant aux particularités de l'image. Ceci est rendu possible par un système de ranking des variables (les bandes) qui est optimisé en même temps que le modèle de base: ce faisant, seules les variables importantes pour résoudre le problème sont utilisées par le classifieur. Le manque d'information étiquétée et l'incertitude quant à sa pertinence pour le problème sont à la source des deux modèles suivants, basés respectivement sur l'apprentissage actif et les méthodes semi-supervisées: le premier permet d'améliorer la qualité d'un ensemble d'entraînement par interaction directe entre l'utilisateur et la machine, alors que le deuxième utilise les pixels non étiquetés pour améliorer la description des données disponibles et la robustesse du modèle. Enfin, le dernier modèle proposé considère la question plus théorique de la structure entre les outputs: l'intègration de cette source d'information, jusqu'à présent jamais considérée en télédétection, ouvre des nouveaux défis de recherche. Advanced kernel methods for remote sensing image classification Devis Tuia Institut de Géomatique et d'Analyse du Risque September 2009 Abstract The technical developments in recent years have brought the quantity and quality of digital information to an unprecedented level, as enormous archives of satellite images are available to the users. However, even if these advances open more and more possibilities in the use of digital imagery, they also rise several problems of storage and treatment. The latter is considered in this Thesis: the processing of very high spatial and spectral resolution images is treated with approaches based on data-driven algorithms relying on kernel methods. In particular, the problem of image classification, i.e. the categorization of the image's pixels into a reduced number of classes reflecting spectral and contextual properties, is studied through the different models presented. The accent is put on algorithmic efficiency and the simplicity of the approaches proposed, to avoid too complex models that would not be used by users. The major challenge of the Thesis is to remain close to concrete remote sensing problems, without losing the methodological interest from the machine learning viewpoint: in this sense, this work aims at building a bridge between the machine learning and remote sensing communities and all the models proposed have been developed keeping in mind the need for such a synergy. Four models are proposed: first, an adaptive model learning the relevant image features has been proposed to solve the problem of high dimensionality and collinearity of the image features. This model provides automatically an accurate classifier and a ranking of the relevance of the single features. The scarcity and unreliability of labeled. information were the common root of the second and third models proposed: when confronted to such problems, the user can either construct the labeled set iteratively by direct interaction with the machine or use the unlabeled data to increase robustness and quality of the description of data. Both solutions have been explored resulting into two methodological contributions, based respectively on active learning and semisupervised learning. Finally, the more theoretical issue of structured outputs has been considered in the last model, which, by integrating outputs similarity into a model, opens new challenges and opportunities for remote sensing image processing.

Psychodynamic interventions in cancer care II: a qualitative analysis of the therapists' reports.

BACKGROUND: To investigate the focus of psychodynamic-oriented interventions in cancer patients by means of a qualitative analysis of the therapists' reports. METHODS: One hundred thirty-five reports collected within a controlled psychotherapy trial were analyzed; the themes addressed during the intervention were classified in categories reflecting the focus of the intervention and correlated with sociodemographic and medical data and type of intervention. RESULTS: Twenty main themes were identified and classified in two categories: category 1 corresponded to interventions based on expression and support, and category 2 to interventions based on introspection, with subcategory 2.1 focusing on the patient's psychological functioning and subcategory 2.2 focusing on his way to engage and communicate in relationships. While the most frequently addressed theme was related to the diagnosis of cancer (N = 102/576; 22.6%), the majority of themes were related to other concerns (N = 446/576; 77.4%). Half of the interventions (50.4%) were classified in category 1, 27.4% in category 2.1, and 9.6% in category 2.2. Patients of category 1 entered less often brief psychotherapy (step 2 of the intervention) and more frequently suffered from advances disease. CONCLUSIONS: A wide variety of themes are addressed in psychodynamic interventions in the oncology setting, illustrating that cancer is not the only focus of therapy. Other themes reflect different psychological difficulties triggered by the disease. This study illustrates that cancer patients have different needs, which surpass the event of the disease. Early clarification and comprehension of the demand may therefore be beneficial to adjust the therapeutic approach. Copyright © 2013 John Wiley & Sons, Ltd.

Interprofessional practices of physiotherapists working with adults with low back pain in Québec's private sector: results of a qualitative study.

BACKGROUND: Collaboration and interprofessional practices are highly valued in health systems, because they are thought to improve outcomes of care for persons with complex health problems, such as low back pain. Physiotherapists, like all health providers, are encouraged to take part in interprofessional practices. However, little is known about these practices, especially for private sector physiotherapists. This study aimed to: 1) explore how physiotherapists working in the private sector with adults with low back pain describe their interprofessional practices, 2) identify factors that influence their interprofessional practices, and 3) identify their perceived effects. METHODS: Participants were 13 physiotherapists, 10 women/3 men, having between 3 and 21 years of professional experience. For this descriptive qualitative study, we used face-to-face semi-structured interviews and conducted content analysis encompassing data coding and thematic regrouping. RESULTS: Physiotherapists described interprofessional practices heterogeneously, including numerous processes such as sharing information and referring. Factors that influenced physiotherapists' interprofessional practices were related to patients, providers, organizations, and wider systems (e.g. professional system). Physiotherapists mostly viewed positive effects of interprofessional practices, including elements such as gaining new knowledge as a provider and being valued in one's own role, as well as improvements in overall treatment and outcome. CONCLUSIONS: This qualitative study offers new insights into the interprofessional practices of physiotherapists working with adults with low back pain, as perceived by the physiotherapists' themselves. Based on the results, the development of strategies aiming to increase interprofessionalism in the management of low back pain would most likely require taking into consideration factors associated with patients, providers, the organizations within which they work, and the wider systems.

Instruments for investigating fitness to drive - needs and expectations in primary care: a qualitative study

Background: Primary care physicians are often requested to assess their patients' fitness to drive. Little is however known on their needs to help them in this task. Aims: The aim of this study is to develop theories on needs, expectations, and barriers for clinical instruments helping physicians assess fitness to drive in primary care. Methods: This qualitative study used semi-structured interviews to investigate needs and expectations for instruments used to assess fitness to drive. From August 2011 to April 2013, we recorded opinions from five experts in traffic medicine, five primary care physicians, and five senior drivers. All interviews were integrally transcribed. Two independent researchers extracted, coded, and stratified categories relying on multi-grounded theory. All participants validated the final scheme. Results: Our theory suggests that for an instruments assessing fitness to drive to be implemented in primary care, it need to contribute to the decisional process. This requires at least five conditions: 1) it needs to reduce the range of uncertainty, 2) it needs to be adapted to local resources and possibilities, 3) it needs to be accepted by patients, 4) choices of tasks need to adaptable to clinical conditions, 5) and interpretation of results need to remain dependant of each patient's context. Discussion and conclusions: Most existing instruments assessing fitness to drive are not designed for primary care settings. Future instruments should also aim to support patient-centred dialogue, help anticipate driving cessation, and offer patients the opportunity to freely take their own decision on driving cessation as often as possible.

Detecting, quantifying and adjusting for publication bias in meta-analyses: protocol of a systematic review on methods.

BACKGROUND: Health professionals and policymakers aspire to make healthcare decisions based on the entire relevant research evidence. This, however, can rarely be achieved because a considerable amount of research findings are not published, especially in case of 'negative' results - a phenomenon widely recognized as publication bias. Different methods of detecting, quantifying and adjusting for publication bias in meta-analyses have been described in the literature, such as graphical approaches and formal statistical tests to detect publication bias, and statistical approaches to modify effect sizes to adjust a pooled estimate when the presence of publication bias is suspected. An up-to-date systematic review of the existing methods is lacking. METHODS/DESIGN: The objectives of this systematic review are as follows:âeuro¢ To systematically review methodological articles which focus on non-publication of studies and to describe methods of detecting and/or quantifying and/or adjusting for publication bias in meta-analyses.âeuro¢ To appraise strengths and weaknesses of methods, the resources they require, and the conditions under which the method could be used, based on findings of included studies.We will systematically search Web of Science, Medline, and the Cochrane Library for methodological articles that describe at least one method of detecting and/or quantifying and/or adjusting for publication bias in meta-analyses. A dedicated data extraction form is developed and pilot-tested. Working in teams of two, we will independently extract relevant information from each eligible article. As this will be a qualitative systematic review, data reporting will involve a descriptive summary. DISCUSSION: Results are expected to be publicly available in mid 2013. This systematic review together with the results of other systematic reviews of the OPEN project (To Overcome Failure to Publish Negative Findings) will serve as a basis for the development of future policies and guidelines regarding the assessment and handling of publication bias in meta-analyses.

Qualitative grading of severity of lumbar spinal stenosis based on the morphology of the dural sac on magnetic resonance images.

STUDY DESIGN.: Retrospective radiologic study on a prospective patient cohort. OBJECTIVE.: To devise a qualitative grading of lumbar spinal stenosis (LSS), study its reliability and clinical relevance. SUMMARY OF BACKGROUND DATA.: Radiologic stenosis is assessed commonly by measuring dural sac cross-sectional area (DSCA). Great variation is observed though in surfaces recorded between symptomatic and asymptomatic individuals. METHODS.: We describe a 7-grade classification based on the morphology of the dural sac as observed on T2 axial magnetic resonance images based on the rootlet/cerebrospinal fluid ratio. Grades A and B show cerebrospinal fluid presence while grades C and D show none at all. The grading was applied to magnetic resonance images of 95 subjects divided in 3 groups as follows: 37 symptomatic LSS surgically treated patients; 31 symptomatic LSS conservatively treated patients (average follow-up, 2.5 and 3.1 years); and 27 low back pain (LBP) sufferers. DSCA was also digitally measured. We studied intra- and interobserver reliability, distribution of grades, relation between morphologic grading and DSCA, as well relation between grades, DSCA, and Oswestry Disability Index. RESULTS.: Average intra- and interobserver agreement was substantial and moderate, respectively (k = 0.65 and 0.44), whereas they were substantial for physicians working in the study originating unit. Surgical patients had the smallest DSCA. A larger proportion of C and D grades was observed in the surgical group. Surface measurementsresulted in overdiagnosis of stenosis in 35 patients and under diagnosis in 12. No relation could be found between stenosis grade or DSCA and baseline Oswestry Disability Index or surgical result. C and D grade patients were more likely to fail conservative treatment, whereas grades A and B were less likely to warrant surgery. CONCLUSION.: The grading defines stenosis in different subjects than surface measurements alone. Since it mainly considers impingement of neural tissue it might be a more appropriate clinical and research tool as well as carrying a prognostic value.

From dialysis to transplantation, illness experience and patients' concerns about future: A longitudinal qualitative study

Background: Transplantation is the treatment of choice when compared to dialysis. Long-term evolution of patients is rarely comprehensively described. Thirty end-stage renal disease patient's experience of illness was explored from registration for transplantation until twenty-four months after transplantation. Methods: Longitudinal semi-structured interviews were conducted, and qualitative discourse analysis performed. Findings: Before transplantation loss of quality of life (QOL), emotional fragility related to dialysis constraints were reported, and increased with waiting-time. Six months after transplantation, recovered freedom was described but acute rejection, and life-dependency to immunosuppressants generated concerns. After twelve months, long-term survival of the graft, and possible return-to-dialysis were mentioned. After twenty months graft's dysfunction, co-morbidities, immunosuppressants side effects rose concerns even though QOL persisted. Most patients report positive transformations after transplantation, which are related to graft survival and limited co-morbidities. Discussion: As time passes, patients deal with changing illness constraints, and contemplate with anxiety possible new return to dialysis and/or transplantation.

Evaluation and comparison of current fetal ultrasound image segmentation methods for biometric measurements: a grand challenge.

This paper presents the evaluation results of the methods submitted to Challenge US: Biometric Measurements from Fetal Ultrasound Images, a segmentation challenge held at the IEEE International Symposium on Biomedical Imaging 2012. The challenge was set to compare and evaluate current fetal ultrasound image segmentation methods. It consisted of automatically segmenting fetal anatomical structures to measure standard obstetric biometric parameters, from 2D fetal ultrasound images taken on fetuses at different gestational ages (21 weeks, 28 weeks, and 33 weeks) and with varying image quality to reflect data encountered in real clinical environments. Four independent sub-challenges were proposed, according to the objects of interest measured in clinical practice: abdomen, head, femur, and whole fetus. Five teams participated in the head sub-challenge and two teams in the femur sub-challenge, including one team who tackled both. Nobody attempted the abdomen and whole fetus sub-challenges. The challenge goals were two-fold and the participants were asked to submit the segmentation results as well as the measurements derived from the segmented objects. Extensive quantitative (region-based, distance-based, and Bland-Altman measurements) and qualitative evaluation was performed to compare the results from a representative selection of current methods submitted to the challenge. Several experts (three for the head sub-challenge and two for the femur sub-challenge), with different degrees of expertise, manually delineated the objects of interest to define the ground truth used within the evaluation framework. For the head sub-challenge, several groups produced results that could be potentially used in clinical settings, with comparable performance to manual delineations. The femur sub-challenge had inferior performance to the head sub-challenge due to the fact that it is a harder segmentation problem and that the techniques presented relied more on the femur's appearance.

Can smartphones and tablets improve the management of childhood illness in Tanzania? A qualitative study from a primary health care worker's perspective.

BACKGROUND: The impact of the Integrated Management of Childhood Illness (IMCI) strategy has been less than anticipated because of poor uptake. Electronic algorithms have the potential to improve quality of health care in children. However, feasibility studies about the use of electronic protocols on mobile devices over time are limited. This study investigated constraining as well as facilitating factors that influence the uptake of a new electronic Algorithm for Management of Childhood Illness (ALMANACH) among primary health workers in Dar es Salaam, Tanzania. METHODS: A qualitative approach was applied using in-depth interviews and focus group discussions with altogether 40 primary health care workers from 6 public primary health facilities in the three municipalities of Dar es Salaam, Tanzania. Health worker's perceptions related to factors facilitating or constraining the uptake of the electronic ALMANACH were identified. RESULTS: In general, the ALMANACH was assessed positively. The majority of the respondents felt comfortable to use the devices and stated that patient's trust was not affected. Most health workers said that the ALMANACH simplified their work, reduced antibiotic prescription and gave correct classification and treatment for common causes of childhood illnesses. Few HWs reported technical challenges using the devices and complained about having had difficulties in typing. Majority of the respondents stated that the devices increased the consultation duration compared to routine practice. In addition, health system barriers such as lack of staff, lack of medicine and lack of financial motivation were identified as key reasons for the low uptake of the devices. CONCLUSIONS: The ALMANACH built on electronic devices was perceived to be a powerful and useful tool. However, health system challenges influenced the uptake of the devices in the selected health facilities.